IDEAS home Printed from https://ideas.repec.org/a/eee/eneeco/v131y2024ics0140988324000872.html
   My bibliography  Save this article

Inverse product differentiation logit model: Holy grail or not?

Author

Listed:
  • Huo, Jinghai
  • Dua, Rubal
  • Bansal, Prateek

Abstract

Random coefficient logit (RCL) is the workhorse model to estimate demand elasticities in markets with differentiated products using aggregated sales data. While the ability to represent flexible substitution patterns makes RCL preferable, its estimation is computationally challenging due to the numerical inversion of the demand function. The recently proposed inverse product differentiation logit (IPDL) addresses this computational issue by directly specifying the inverse demand function. In addition to computational gains, IPDL claims to maintain flexibility through non-hierarchical product segmentation across multiple characteristics. Thus, IPDL is an attractive alternative to RCL in theory, but its potential remains unexplored in empirical studies. We present the first application of IPDL in understanding the demand for passenger cars in China using province-level sales data. Our results show that IPDL is around 300 times faster than RCL, can capture complementarity patterns that cannot be captured by RCL, can identify substitution patterns as well as RCL, and outperforms RCL in goodness of fit measures.

Suggested Citation

  • Huo, Jinghai & Dua, Rubal & Bansal, Prateek, 2024. "Inverse product differentiation logit model: Holy grail or not?," Energy Economics, Elsevier, vol. 131(C).
    • Handle: RePEc:eee:eneeco:v:131:y:2024:i:c:s0140988324000872
    DOI: 10.1016/j.eneco.2024.107379
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0140988324000872
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.eneco.2024.107379?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Steven T. Berry, 1994. "Estimating Discrete-Choice Models of Product Differentiation," RAND Journal of Economics, The RAND Corporation, vol. 25(2), pages 242-262, Summer.
    2. Cardell, N. Scott, 1997. "Variance Components Structures for the Extreme-Value and Logistic Distributions with Application to Models of Heterogeneity," Econometric Theory, Cambridge University Press, vol. 13(2), pages 185-213, April.
    3. Laura Grigolon & Frank Verboven, 2014. "Nested Logit or Random Coefficients Logit? A Comparison of Alternative Discrete Choice Models of Product Differentiation," The Review of Economics and Statistics, MIT Press, vol. 96(5), pages 916-935, December.
    4. Berry, Steven & Levinsohn, James & Pakes, Ariel, 1995. "Automobile Prices in Market Equilibrium," Econometrica, Econometric Society, vol. 63(4), pages 841-890, July.
    5. Christopher Conlon & Jeff Gortmaker, 2020. "Best practices for differentiated products demand estimation with PyBLP," RAND Journal of Economics, RAND Corporation, vol. 51(4), pages 1108-1161, December.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Mogens Fosgerau & Julien Monardo & André de Palma, 2024. "The Inverse Product Differentiation Logit Model," American Economic Journal: Microeconomics, American Economic Association, vol. 16(4), pages 329-370, November.
    2. Doi, Naoshi, 2022. "A simple method to estimate discrete-type random coefficients logit models," International Journal of Industrial Organization, Elsevier, vol. 81(C).
    3. Brett Hollenbeck & Kosuke Uetake, 2021. "Taxation and market power in the legal marijuana industry," RAND Journal of Economics, RAND Corporation, vol. 52(3), pages 559-595, September.
    4. Marc Ivaldi & Jiekai Zhang, 2017. "Advertising Competition in the Free-to-Air TV Broadcasting Industry," CESifo Working Paper Series 6461, CESifo.
    5. Laura Grigolon, 2021. "Blurred boundaries: A flexible approach for segmentation applied to the car market," Quantitative Economics, Econometric Society, vol. 12(4), pages 1273-1305, November.
    6. P. Givord & C. Grislain-Letrémy & H. Naegele, 2014. "How does fuel taxation impact new car purchases? An evaluation using French consumer-level dataset," Documents de Travail de l'Insee - INSEE Working Papers g2014-14, Institut National de la Statistique et des Etudes Economiques.
    7. Ivaldi, Marc & Zhang, Jiekai, 2015. "Advertising Competition in the French Free-To-Air Television Broadcasting Industry," CEPR Discussion Papers 10762, C.E.P.R. Discussion Papers.
    8. Pauline Givord & Céline Grislain-Letrémy & Helene Naegele, 2014. "How Does Fuel Taxation Impact New Car Purchases?: An Evaluation Using French Consumer-Level Data," Discussion Papers of DIW Berlin 1428, DIW Berlin, German Institute for Economic Research.
    9. Bokhari, Farasat A.S. & Mariuzzo, Franco, 2018. "Demand estimation and merger simulations for drugs: Logits v. AIDS," International Journal of Industrial Organization, Elsevier, vol. 61(C), pages 653-685.
    10. Javier Donna & Andre Trindade & Pedro Pereira & Tiago Pires, 2018. "Measuring the Welfare of Intermediation in Vertical Markets," 2018 Meeting Papers 984, Society for Economic Dynamics.
    11. Givord, Pauline & Grislain-Letrémy, Céline & Naegele, Helene, 2018. "How do fuel taxes impact new car purchases? An evaluation using French consumer-level data," Energy Economics, Elsevier, vol. 74(C), pages 76-96.
    12. Øyvind Thomassen & Howard Smith & Stephan Seiler & Pasquale Schiraldi, 2017. "Multi-category Competition and Market Power: A Model of Supermarket Pricing," American Economic Review, American Economic Association, vol. 107(8), pages 2308-2351, August.
    13. Doan, Thanh & Manenti, Fabio M. & Mariuzzo, Franco, 2023. "Reprint of: Platform competition in the tablet PC market: The effect of application quality," International Journal of Industrial Organization, Elsevier, vol. 89(C).
    14. Sarig, Oren, 2024. "Pharmaceutical demand response to utilization management," Journal of Health Economics, Elsevier, vol. 93(C).
    15. Malina, Christiane, 2016. "The environmental impact of vehicle circulation tax reform in Germany," CAWM Discussion Papers 86, University of Münster, Münster Center for Economic Policy (MEP).
    16. Enghin Atalay & Erika Frost & Alan T. Sorensen & Christopher J. Sullivan & Wanjia Zhu, 2023. "Scalable Demand and Markups," NBER Working Papers 31230, National Bureau of Economic Research, Inc.
    17. Takeshi Fukasawa, 2024. "Fast and simple inner-loop algorithms of static / dynamic BLP estimations," Papers 2404.04494, arXiv.org, revised Oct 2024.
    18. Nurski, Laura & Verboven, Frank, 2014. "Incumbency advantages, distribution networks and exclusivity — Evidence from the European car markets," International Journal of Industrial Organization, Elsevier, vol. 34(C), pages 75-79.
    19. Donna, Javier D. & Pereira, Pedro & Pires, Tiago & Trindade, Andre, 2018. "Measuring the Welfare of Intermediaries in Vertical Markets," MPRA Paper 90465, University Library of Munich, Germany.
    20. Rebecca Cleary & Jean-Paul Chavas, 2022. "Strategic supermarket pricing of private labels and manufacturer brands," Empirical Economics, Springer, vol. 62(6), pages 2921-2950, June.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:eneeco:v:131:y:2024:i:c:s0140988324000872. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/eneco .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.